Athletic recovery system combining cognitive and physical assessments

ABSTRACT

A method for cognitive brain training, psychological motivation, and recovery to be used in conjunction with physical exercise in order to reduce the effects of mental and physical fatigue and improve athletic performance. A plurality of input devices integrate ergonomically with different sports so as not to limit movement, eye-hand coordination or negatively impact physical training. Software, executable on a portable computing device is configured for a sport, enabling an athlete to perform physical and cognitive tasks at the same time. Metrics, formulas and algorithms combine the athlete&#39;s self-rated performance with real-time cognitive and physiological output metrics to provide reports of the athlete&#39;s performance for each workout and for all workouts overtime. Mental recovery and motivation protocols used to help athletes stay on task and recover from the physical training. Cognitive fatigue self-assessment tests used to help athletes determine their current level of mental fatigue and readiness to train.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/799,458, filed on Feb. 24, 2020, entitled “ATHLETIC TRAINING SYSTEMCOMBINING COGNITIVE TASKS WITH PHYSICAL TRAINING,” which claims priorityto and the benefit under 35 U.S.C. § 119(e) of U.S. ProvisionalApplication Ser. No. 62/809,927, filed on Feb. 25, 2019, entitled“METHOD AND APPARATUS FOR IMPROVING ATHLETIC PERFORMANCE BY COMBININGCOGNITIVE TASKS AND MOTIVATION TECHNIQUES WITH PHYSICAL TRAINING AT THESAME TIME.” The contents of these applications are incorporated hereinby reference in their entirety.

TECHNICAL FIELD

This patent application relates generally to sports science,neuroscience and psychology, and more particularly to sportsneuropsychology. This patent application relates more specifically to anathletic training system.

BACKGROUND

In the traditional physiological model of athletic training, themethodology to improve athletic performance and reduce the negativeimpacts of fatigue is grounded in the assertion that achieving thehighest level of performance is limited by an individual's specificphysiological, metabolic and biomechanical capacity. Therefore, thisphysiological model of athletic training has historically been focusedon improving the individual's cardiorespiratory and anaerobic capacityby utilizing a variety of task-oriented physical conditioning techniquesas a stimulus for physiological adaptation.

Research has been conducted on improving an athlete's overallperformance as a result of cognitive tasks combined with physicaltraining. See, Marcora, Samuele M. et al, “Mental fatigue impairsphysical performance in humans”, Journal of Applied Physiology, 2009, v.106, n. 3, p. 857-864., Pageaux, B., Lepers, R., Dietz, K. C. et al,“Response inhibition impairs subsequent self-paced enduranceperformance”, European Journal of Applied Physiology, 2014, v. 114, n.5, p. 1095-1105., Martin, Kristy et al, “Superior Inhibitory Control andResistance to Mental Fatigue in Professional Road Cyclists”, PloS one,2016, 11(7): e0159907.

Some of that research has been based on training the brain withinhibitory control tests during exercise to improve physical performanceover time. See, Staiano, Walter et al, “A Randomized Controlled Trial ofBrain Endurance Training (BET) to Reduce Fatigue During EnduranceExercise”, paper presented at: American College of Sports Medicine(ACSM) Annual Meeting: San Diego, May 2015., Staiano, Walter et al,“Impact of 4-week Brain Endurance Training (BET) on Cognitive andPhysical Performance in Professional Football Players: 3504 Board #192June 1 8:00 AM-9:30 AM”, Medicine & Science in Sports & Exercise, 2019,v. 51, n. 6, p. 964. Additionally, research has also confirmed thatusing motivational self-talk in conjunction with exercise enhancesathletic performance. See, Blanchfield, Anthony et al, “Talking YourselfOut of Exhaustion: The Effects of Self-talk on Endurance Performance”,Medicine & Science in Sports & Exercise, 2014, v. 46, n. 5, p. 998-1007.

Other research has shown that other cognitive recovery protocols may beused to reduce the effects of cognitive fatigue such as listening toBinaural beats, guided breathing, subliminal priming and other suchprotocols. See, Axelsen, J. L. et al, “On-the-Spot Binaural Beats andMindfulness Reduces the Effect of Mental Fatigue”, Journal of CognitiveEnhancement, 2020, OnlineFirst, 1-9.

Cognitive assessment for medical and psychological testing is known, butassessment techniques used for these purposes are poorly suited forconducting cognitive tasks during exercise. For example, prior art inthese fields cannot be practically used by athletes during trainingbecause they require the use of a computer keypad or keyboard for theinput of cognitive tasks. This type of solution is not practical orcommercially viable as it would require the athlete to assume unnaturalpositions in order to interact with a keyboard and computer whileperforming the physical training with the cognitive task. Examples ofsuch prior art within the medical, psychology and cognitive assessmentfields include: U.S. Pat. No. 5,911,581, issued to Reynolds, et al. onJun. 15, 1999; U.S. Pat. No. 6,416,472, issued to Cady, et al. on Jul.9, 2002; U.S. Pat. No. 10,380,910, issued to Wu, et al. on Aug. 13,2019; disclose various solutions conducting and measuring the results ofcognitive tests using a computer and keypad or keyboard.

Within the sports domain prior art that efforts to combine sportstraining and cognitive function have one or more drawbacks. Examples ofsuch prior attempts may be found in: U.S. Pat. No. 20090281450, issuedto Reichow, et al. on Nov. 12, 2009; U.S. Pat. No. 10,478,698, issued toTinjust on Nov. 19, 2019. These references disclose systems used forcognitive tasks during physical training. However, the inventors haverecognized that the disclosed approaches suffer from severaldisadvantages for improving athletic performance. For example, they donot contemplate the neuropsychological model of cognitive and physicaltraining and therefore do not incorporate cognitive tasks that, whencombined with physical exercise, are effective at inducing mentalfatigue and creating a cognitive performance adaptation over time.Additionally, these references do not provide ergonomic input devicesfor cognitive testing that can be easily adapted to a plurality ofsports without compromising range of motion, eye-hand coordination,athletic form or safety. Further, they do not contemplate othercognitive solutions to improve performance, such as incorporatingcognitive recovery protocols and psychological-based motivationtechniques.

BRIEF SUMMARY

Inventive concepts as described herein may be embodied as an athletictraining system for improving athletic performance by combiningcognitive tasks with physical training. The system may comprise a userinput device configured to send messages to a computer and a computerconfigured to receive messages from the input device corresponding tocognitive tasks. The computer may comprise at least one processor, auser interface; and computer-storage medium storing computer executableinstructions that, when executed by the at least one processor, conduct,via the user interface display of the computer and the user inputdevice, a cognitive training session. The computer-executableinstructions may comprise a self-calibration component configured torecord an athlete's cognitive and physical output; a first interfacecomponent configured to receive user input selecting from a plurality ofcognitive and physical workout options; a second interface componentconfigured to provide output guiding a user through both cognitive andphysical tasks within the same workout; a self-rating componentconfigured to assess cognitive and physical fatigue based on one or moreinputs; a third interface component configured to provide real-timephysical and cognitive metrics based on an evaluation of the athlete'sperformance; an evaluation component configured to provide a summary ofthe athlete's cognitive and physical training performance results.

In another aspect, the inventive concepts as described herein may beembodied as a method of operating an athletic training system forproviding a plurality of cognitive and physical recovery protocols. Themethod may comprise receiving through an interface user input selectingfrom a plurality of cognitive and physical recovery options; presentingan interface that combines multiple recovery protocols in a singleinterface; capturing at least one physiological metric as part of arecovery evaluation process; assessing level of cognitive and physicalstress of a user based on input provided by the user; and providing asummary of the user's cognitive and physical recovery results.

In another aspect, the inventive concepts as described herein may beembodied as a method of operating an athletic training system forimproving athletic performance by combining cognitive tasks withphysical training. The method may comprise: presenting through a userinterface cognitive tasks for a user to perform; and during a trainingsession, adapting difficulty of the cognitive tasks.

The foregoing any other techniques as described herein may be usedseparately or together in a combination of any two or more of thosetechniques.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1A illustrates an exemplary embodiment of a tactile-based inputapparatus that includes waterproof, ergonomic, pressure sensitivebuttons that attach to the body or training machine.

FIG. 1B illustrates an exemplary embodiment of a tactile-based inputapparatus with button and strap in exploded view.

FIG. 1C illustrates an exemplary embodiment of a tactile-based inputapparatus with buttons and straps to be attached to bicycle handlebars.

FIG. 1D illustrates an exemplary embodiment of a tactile-based inputapparatus with buttons and straps to be held in the hands.

FIG. 2 Illustrates an exemplary embodiment of a gesture-based inputapparatus version that includes waterproof, ergonomic sensors attachedto the body or training machine.

FIG. 3 illustrates an exemplary embodiment of a software supporting avoice-based input version to capture commands from an athlete using aportable computing device such as a smartphone or desktop computer.

FIG. 4 illustrates an exemplary embodiment of a software supporting theinput apparatus devices to connect wirelessly with a portable computingdevice such as a smartphone or desktop computer.

FIG. 5 illustrates an exemplary embodiment of a user interfacesupporting the selection, delivery and recording of various cognitiveand physical workout programs.

FIG. 6 illustrates an exemplary embodiment of a user interfacesupporting a self-rating calibration system to be completed by athletesat the start of the workout using a computing device such as asmartphone or desktop computer, shown here executing on a portabledevice mounted on exercise equipment.

FIG. 7 illustrates an exemplary embodiment of a user interfacesupporting cognitive training interfaces displayed on a portablecomputing device such as a smartphone or desktop computer.

FIG. 8 illustrates an exemplary embodiment of a user interfacesupporting the reception and translation of coded messages sentwirelessly from the input apparatus device to a portable computingdevice running the custom application.

FIG. 9 illustrates an exemplary embodiment of a user interfacesupporting real time physiological and cognitive output metrics capturedand displayed during training on a portable computing device such as asmartphone or desktop computer.

FIG. 10 illustrates an exemplary embodiment of a user interfacesupporting a quantitative and qualitative self-rating system to becompleted by athletes at the end of the workout using a computing devicesuch as a smartphone or desktop computer.

FIG. 11 illustrates an exemplary embodiment of a user interfacesupporting cognitive and physiological performance metrics, formulas andalgorithms to be recorded and calculated using a computing device suchas a smartphone or desktop computer.

FIG. 12 illustrates an exemplary embodiment of a user interfacesupporting cognitive and physiological performance reports includingworkout history and performance over time for all workouts using acomputing device such as a smartphone or desktop computer.

FIG. 13 illustrates an exemplary embodiment of a user interfacesupporting lookup tables designed to compare an athlete's self-ratedperformance with physiological and cognitive output measurementscaptured during training using a computing device such as a smartphoneor desktop computer.

FIG. 14 illustrates an exemplary embodiment of a user interfacesupporting positive self-talk mantras that are displayed during trainingsessions using a portable computing device such as a smartphone.

FIG. 15 illustrates an exemplary embodiment of a user interfacesupporting the configuration and personalization of positive self-talkmantras that are displayed during training sessions using a computingdevice such as a smartphone or desktop computer.

FIG. 16A illustrates an exemplary embodiment of a user interfacesupporting the integration of various cognitive recovery protocols forimproving motivation and physical and mental recovery.

FIG. 16B illustrates an exemplary embodiment of a user interfacesupporting the integration of various cognitive recovery protocols forimproving motivation and physical and mental recovery.

FIG. 17 illustrates an exemplary embodiment of a user interfacesupporting cognitive and physiological recovery metrics, formulas andalgorithms to be recorded and calculated using a computing device suchas a smartphone or desktop computer.

FIG. 18A illustrates an exemplary embodiment of a user interfacesupporting a cognitive fatigue self-assessment system to be completedregularly by athletes to determine their current level of mental fatiguecompared to their baseline.

FIG. 18B illustrates an exemplary embodiment of a user interfacesupporting a cognitive fatigue self-assessment system to be completedregularly by athletes to determine their current level of mental fatiguecompared to their baseline.

FIG. 19 is a simplified flow diagram of a method of operating softwareto perform brain training according to some embodiments.

DETAILED DESCRIPTION

The inventors have recognized and appreciated designs for an athletictraining system, including apparatus and software, that aids athletes inenhancing their physical performance by incorporating aneuropsychological model for cognitive brain training in conjunctionwith physical exercise.

In some embodiments, the apparatus and/or software may be based oncognitive brain training through tasks that have been shown to activatethe area of the brain associated with mental fatigue known as theanterior cingulate cortex (ACC) found within the prefrontal cortex. Insome embodiments, the neuropsychological cognitive tasks that are usedinclude the Stroop Task, Psychomotor Vigilance Task (PVT), Go/No GoTask, Continuous Performance Task (CPT), Stop Signal Task (SST) and/orother similar tasks. One or more such tasks, which require a continuedlevel of focus and inhibitory control creating a mentally fatigued statein the athlete, may be performed in conjunction with physical exercisein order to create adaptation and improve resilience to mental fatiguewith continued practice by the athlete.

In contrast to known research set-ups, an athletic training enhancementsystem as described herein may be practical and commercially viable asit does not require an athlete to assume unnatural positions in order tointeract with computer input and output devices while performing thephysical task. Rather, in accordance with some embodiments, an ergonomicinput device may be used for cognitive tasks in conjunction withphysical exercise across a plurality of different sports withoutcompromising range of motion, eye-hand or athletic form. Techniques asdescribed herein are amenable to implementation so as to be easilyportable or extensible to different sports and physical movementmodalities. In some embodiments, the disclosed techniques may beextended to sports that require both a free range of motion and eye-handcoordination, such as cycling, strength training, rowing, swimming,running, rugby and basketball.

In some embodiments, a simple and portable user interface device, suchas a button or other sensor that detects movement of a portion of auser's body, may interface with a computer executing software thatprocesses inputs and generates outputs to implement an athletic trainingsystem. The user interface may be integrated with a support structure sothat it may be worn by a user or attached to a piece of athleticequipment. A button, for example, may be attached to a strap, which auser may hold or may be mounted to equipment, such as a bicyclehandlebar. Alternatively or additionally, a sensor may be integratedinto an item worn by a user, such as a glove or other piece of clothingor a wrist band.

In some embodiment's, a training enhancement system may alternatively oradditionally provide user stimulus based on motivational techniques andcognitive recovery protocols, which may also be used in conjunction withphysical training.

In some embodiments, a training enhancement system may perform acognitive fatigue assessment to help the athlete calibrate their levelof daily training activity.

I. Computing Systems

The systems and methods described herein rely on a variety of computersystems, networks and/or digital devices for operation. In order tofully appreciate how the system operates, an understanding of suitablecomputing devices and systems is useful. The computing devices, systemsand methods disclosed herein are enabled as a result of application viaa suitable computing device (including without limitation mobile devicessuch as smartphones and tablets). In at least some configurations, auser executes a browser on a computer to view digital content items on adisplay associated with the computer. Digital content may be stored orgenerated on the computer or may be accessed from a remote location. Forexample, a computer can obtain content by connecting to a front endserver via a network, which is typically the Internet, but can also beany network, including but not limited to a mobile, wired or wirelessnetwork, a private network, or a virtual or ad hoc private network. Aswill be understood very large numbers (e.g., millions) of users aresupported and can be in communication with the website at any time. Theuser may utilize a variety of different computing devices. Examples ofuser devices include, but are not limited to, personal computers,digital assistants, personal digital assistants, cellular phones, mobilephones, smart phones, tablets or laptop computers. The browser caninclude any application that allows users to access web pages on theWorld Wide Web. Suitable applications include, but are not limited to,Chrome®, Brave®, Firefox®, Microsoft Edge®, Apple®, Safari or anyapplication capable of or adaptable to allowing access to web pages onthe World Wide Web. Primarily, a user may download an app, e.g., ontothe user's portable computing device, in order to perform brain trainingand mental recovery tasks on the user's hand held device or other usercomputing device.

A computer may have one or more processors that may executecomputer-executable instructions stored in non-transitorycomputer-readable storage media, such as volatile or non-volatilememory. A computer may have one or more input devices, such as a keypador touch screen for receiving tactile input. The computer may have asound input, such as a microphone, for receiving audible input, such asspeech that may be recognized as commands. The computer alternatively oradditionally may have a camera to receive input in visual form.

Further, the computer may have interfaces, such as a wireless interface,USB port or other I/O port, that may be connected to sensors or otherinput devices. For example, one or more sensors, such as a pulse sensor,sweat sensor or other sensor that provides an output indicative ofphysical activity or exertion may be wirelessly coupled to a computer.

A computer may have one or more output devices, such as a display screenor speaker. The input and output devices may be integrated into onephysical unit or may be coupled to a unit via wires or wirelessconnections.

These components integrated into a or coupled to a computer may beaccessed by programming of the athletic training system to provideoutput to or collect input from a user of the system as describedfurther herein.

II. Cognitive Brain Training

Described herein is a training system for athletes and other users withboth an apparatus and software-based methodology for cognitive braintraining to be done in conjunction with physical exercise. The systemmay have one or more components that interact with a user to reduce theeffects of mental and physical fatigue and improve overall athleticperformance. These components may drive interaction with the user bothbefore, during and after a training session. During a physical trainingsession, the system may guide the user in performing cognitive tasksthat train the user's brain to resist cognitive fatigue. The system mayalso collect inputs about the user's physical exertion and performanceas well as cognitive fatigue, for adapting guidance provided on physicalexertion or adapting cognitive training tasks. The system may alsorender motivational content to the user.

Before a physical training session, the system may collect input fromthe user, including on phrases that the user considers motivational.Inputs may also be collected for calibration of the system.

After a training session, the system may collect inputs indicative ofuser cognitive or physical fatigue, including through self-assessmentinputs, and may output cognitive and physical metrics associated withthe training session.

The following is a detailed description of an exemplary embodiment ofsuch an athletic training system and its use by the athlete inclusive ofall of the components described here in. First an athlete turns on orenables the input device to be used during cognitive training in FIGS.1A-D, 2, 3. In the case of a tactile-based input apparatus embodiment inFIGS. 1A-D, the athlete may attach pressure sensitive buttons 102 andstraps 100 a, to a training machine such as on the handlebars of anindoor bicycle trainer 116 in FIG. 1C by attaching the tactile apparatuswith a clip 114 and strap 100 a or by attaching the tactile-based inputapparatus to their hands 118 in FIG. 1D with pressure sensitive buttons102 and straps 100 b. The tactile-based apparatus device in FIG. 1B ismade up of a large button surface area cap 104, a waterproof topenclosure 106 that covers the printed circuit board (PCB) 108, a battery110 and a waterproof bottom enclosure for the PCB 112, and a strap 100 afor attaching the button to a training machine. In FIG. 4 thetactile-based button 118 then sends wireless signals 130 to a portablecomputing device such as a smartphone 132 or desktop computer running acustom application.

In additional embodiments, such as the gesture-based input apparatusversion 120 in FIG. 2 , the athlete attaches the gesture device 120 tothe hands with motion sensors 122 integrated into a glove, strap orother hand-held device. In FIG. 4 the gesture-based apparatus 120 thensends wireless signals interpreted by software 130 running on a portablecomputing device such as a smartphone 132 or desktop computer. In thecase of the voice-based input version of the embodiment in FIG. 3 , theathlete uses voice commands 124 or other spoken inputs that areinterpreted by the software 126 running on a portable computing devicesuch as a desktop computer or smartphone and ensures that the portablecomputing device's microphone is enabled 128.

After either the tactile button (FIGS. 1A-D), the gesture (FIG. 2 ) orthe voice-based (FIG. 3 ) input device is enabled and (where applicable)connected to the portable computing device, the athlete selects aworkout in FIG. 5 from one of the choices available 134 from within thesoftware application and the workout begins. At the start of theworkout, the athlete may be asked to perform a calibration test (FIG. 6) that records the athlete's perceived level of effort. Perceived effortmay be represented using a point scale system 136 that measures theathlete's rating of perceived exertion (RPE) at different physicaloutput levels such as “17—Very Hard” 138 where the athlete exertsphysical effort to meet that perceived level of effort indicated on thescale 136. As the athlete completes the calibration test, standardphysiological measures from this test are saved into lookup tables forfurther analysis (FIG. 13 ) such as power measured in watts for thefunctional threshold power (FTP) lookup table 182 and heart ratemeasured in beats per minute for the lactate threshold heart rate (LTHR)lookup table 186. In this way, the user's perceived physical effort maybe correlated with measured values before, during and after the workoutin order to track cognitive and physiological performance over time.Additionally, these calibrated measures may be used during a trainingsession to adapt the level of difficultly automatically for variouscognitive tasks based on the user's perceived level of effort. Forexample, if the user's rating of perceived exertion becomes reduced,even with the same amount of physical and cognitive stimuli as priorworkouts, this may indicate a positive adaptation to the cognitivetasks, and the task difficultly may automatically increase or decreasein length, complexity or other stimuli depending upon the training goalor workout selected by the user.

During the workout in FIG. 7 , the athlete is presented with differentcognitive training interfaces based on their training goals featuringvarious neuropsychological tasks that target specific areas of the brainand brain pathways helpful for overcoming cognitive fatigue andimproving athletic performance. For instance, the neuropsychologicaltask known as the Stroop Task 140, is an established task for measuringresponse inhibition and requires the user to have the ability toovercome automatic tendencies in order to respond correctly to eachtask. For example, in a Stroop task the user will be presented with acolor word (e.g., “red”, “green” or other colors) that is presented inone of multiple ink colors (e.g., green, red or other colors). Users areinstructed to respond based upon the ink color of the word, not theidentity of the word itself. When the color and the word are congruent(e.g., “red” in red ink), the natural tendency to read the wordfacilitates performance, resulting in fast and accurate responses. Whenthe color and the word are incongruent (e.g., “red” in green ink), thestrong, natural tendency to read the word must be overcome to respond tothe correct ink color. Similarly, the Stop Signal Task (SST) is also anestablished task for measuring response inhibition and consists of a “gostimuli” such as a series of left or right arrows that users areinstructed to respond quickly to every time they are displayed on thecognitive testing interface. On a subset of the tasks, the go stimulusis followed, after a variable delay, by a “stop signal” such as anaudible beep or upward pointing arrow, to which users are instructed toinhibit their response. In other neuropsychological tasks such as thePsychomotor Vigilance Task (PVT), Go/No Go Task, Continuous PerformanceTask (CPT) users must maintain sustained attention to a specific set ofstimuli such as identifying certain objects that appear and disappear onthe cognitive testing interface as quickly as possible which measure theuser's reaction time, alertness, level of cognitive fatigue and decisionmaking ability. These different neuropsychological tasks are performedin conjunction with physical exercise in order to improve cognitive andphysical performance over time.

In some embodiments, the difficulty of the cognitive tasks may beadapted during a training session. For example, the level of difficultyof the cognitive task may be increased by increasing the level ofcomplexity of the task questions, reducing the amount of time allowedfor each question and/or increasing a target score needed tosuccessfully complete a given cognitive task. In some embodiments,cognitive difficulty may be adapted based on a user's perceived level ofeffort, which may be determined from the calibrated measures of physicalexertion. For example, as a user increases their physical exertion suchthat their perceived level of exertion increases, the cognitivedifficulty of the tasks may be increased.

In some embodiments, a control function relating perceived level ofeffort to cognitive difficulty may be linear. In some embodiments, thelevel of cognitive difficulty may increase step wise as various levelsof perceived effort are reached, but there may nonetheless be a generaltrend that level of cognitive difficulty increases in relation toperceived exertion. In other embodiments, the control function may benon-linear or may be linear over a range of perceived exertion.

Moreover, the control function may be based on parameters in addition toperceived level of effort. Training goals input by a user may be used inthe function. For a user that has specified a higher goal, for example,the increase in cognitive difficulty may be greater for each unity ofincrease in perceived exertion. Alternatively or additionally, time maybe a parameter. For example, the duration of planned workout may impactthe amount of increase in cognitive difficulty, with more increase forshorter workouts or where there is a shorter time remaining in theplanned workout.

As an example of another parameter that may impact the control function,the user's sense cognitive fatigue may be used in setting the level ofcognitive difficulty. As the user's cognitive fatigue increases, thelevel of cognitive difficulty may be increase at a slower rate or may bedecreased in some scenarios.

Further, in some embodiments, the level of cognitive difficulty may alsobe calibrated based on measurement taken before, during or after anexercise session. As described herein, the system may prompt a user toprovide inputs serving as an assessment. That assessment may include aperceived level of cognitive difficulty. During or after presenting oneor more cognitive tasks to the user, the system may prompt the user toprovide an assessment of perceived difficulty of the task. Thisassessment may be performed under different conditions to providedifferent levels of mental challenge such that the variations in thetask may be equated to a perceived level of difficulty for the user.Upon determining, during a training session a desired level of cognitivedifficulty, the appropriate task and conditions of that taskcorresponding to that level of perceived cognitive difficulty may beselected.

These tasks may be configured to be performed by a user with a simpleinput device. For example, the athlete tap the tactile buttons whenusing an input device as pictured in FIGS. 1A-D, make gestures whenusing an input device as pictured in FIG. 2 , or speak voice commandswhen using an input device as pictured in FIG. 3 to input answers tocognitive task prompts. The prompts may be questions as indicated inFIG. 7 . These responses may be received and processed by a customapplication through a series of coded messages transmitted wirelessly130 (FIG. 4 ) or by voice inputs 124 (FIG. 3 ) which are theninterpreted by the software 150 (FIG. 8 ), 126 (FIG. 3 ) in order to betranslated into correct and incorrect answers for the cognitive tasks.The coded messages may take the form of alphanumeric values or phrasesthat correspond to answers to cognitive questions such as “R1” and “L1”150 (FIG. 8 ) or “right” and “left” 126 (FIG. 3 ) that can beinterpreted by the software on the portable computing device to mean “GoRight” input for “R1” or “right” and the “Go Left” input for “L1” or“left” which also correspond to answer buttons on the left 142 and theright 146 side of the cognitive testing interface in FIG. 7 .

While the athlete is performing cognitive tasks they are also givenprompts by the software, which may be provided through a system outputdevice such as a display 144 (FIG. 7 ) and audio and visual prompts thatappear in order to notify the athlete when their thresholds are above orbelow target physiological output goals such as maintaining a specificheart rate or maintaining a specific power output measured in watts.

The prompts may be presented in a format that a user may observe whileperforming a physical task. The notifications may, for example, be largecolored areas or simple graphical symbols, such as progress bars ordials. The notifications may be presented through a display on aportable device that is mounted in a location that the user can observewhile performing physical tasks. In the example of FIG. 8 , a portablecomputing device, such as a smartphone is mounted on the handlebars of abicycle used for training. The smartphone may execute the software thatgenerates notifications and processes responses to them. In someembodiments, the portable electronic device may also serve as an inputdevice, as a user may provide input through a touch interface of thedisplay. However, it is not a requirement that the portable computerdevice be in the user's field of view as in some embodiments,notifications may be provided in other ways, such as audibly, throughvibration of the portable computing device, or wirelessly to a speakeror other output device.

In addition to the display and audio and visual alerts, thephysiological target goals may also be represented visually in the formof a real-time progress bar 152 (FIG. 9 ) that is integrated into thecognitive task questions 140 (FIG. 7 ) so that the athlete can maintainfocus on both their physiological target goals as well as the cognitivetasks at the same time. For example, in the case of the Stroop cognitivetask the progress bar will be attached to the bottom of the primarycolor word that appears on the screen e.g. “PURPLE” 152. In othercognitive tasks the progress bar may be adapted to be attached tovarious shapes or symbols appearing at different locations of thecognitive testing screen so that the athlete can easily keep track oftheir physiological target goals while still focusing on the cognitivetask questions. The progress bar 152 (FIG. 9 ) visually represents theuser's current physiological output percentage compared against theirtarget goals. For example, at rest the progress bar is “empty” with nohighlight color on any portion of the bar 154 showing only a graybackground on the bar which indicates that there is no currentphysiological output being generated by the athlete. When the progressbar is extended to 50% of the allowable space by a highlighted color onthe bar 156 this indicates to the athlete that their current output isonly 50% of their target physiological goal. As the athlete continues toincrease their physiological output in order to match the target goalthe highlighted color portion of the progress bar will continue toextend in length until it reaches 100% of the allowable space 158indicating that the athlete has met the target goal and should maintaintheir current physiological output level in order to ensure that theprogress bar remains fully extended (FIG. 9 ). If the athlete exceedsthe target goal of over 100% the progress bar will highlight in adifferent color on the far right edge of the bar 160 indicating that theathlete should reduce their physiological output in order to achieve thetarget goal of 100% (FIG. 9 ).

Upon the completion of the workout (FIG. 10 ) the athlete is asked toanswer a series of quantitative and qualitative questions to self-ratetheir overall performance including their rating of perceived exertion(RPE) for the workout 162 and several psychological questions 164related to how mentally and physically demanding the workout was forthem. The cognitive training software then uses a series of metrics,formulas and algorithms to combine the athlete's self-rated metrics 162,164 (FIG. 10 ) with the real-time cognitive and physiological outputmetrics 148 (FIG. 7 ) to provide reports that summarize the athlete'sperformance for each workout (FIG. 11 ).

FIG. 11 shows the end of workout report that includes the athlete'sworkout assessment 166, cognitive metrics 168, physical metrics 170 andworkout intervals 172. The sections in FIG. 11 , display criticalcognitive and physical metrics from the workout. Cognitive metrics maybe computed based on user responses received during cognitive tasks,such as total score 168 measured by the total number of correct answersduring all cognitive tasks, reaction time 168 measured by the averagelength of time to respond to each of the cognitive questions correctly,accuracy 168 measured by the percentage of correct answers per intervaland overall, answer rate (RCS) 168 measured by the athlete's totalcorrect answers (per workout) divided by the sum of their reaction time,lapses 168 measured by counting the total number of slower than averageresponses to the brain training tasks. These cognitive metrics may beused to adapt the level of difficultly of cognitive tasks duringsubsequent workouts by automatically increasing or decreasing the levelof complexity of the task questions, increasing or reducing the amountof time allowed for each question and increasing or decreasing thetarget score needed to successfully complete a given cognitive task. Forexample, if the athlete's answer rate (RCS) is consistently better thantheir baseline percentage for more than a predefined number of priorworkouts then the difficultly level of the athlete's cognitive tasks intheir next workout will be increased in order to ensure that they arereceiving the right amount of cognitive stimuli to continually improve.Additionally, within the workout assessment 166 the cognitive metricsmay be used to recommend additional training or recovery sessions basedon the athlete's performance. For example, if the athlete's perceptiongap score is significantly lower in terms of performance from theirbaseline percentage in a given workout then the workout assessment mayinclude a recommendation to temporarily discontinue cognitive trainingand instead increase the number of cognitive recovery sessions in orderto rest and recover before resuming cognitive training.

Physical metrics may be computed based on sensor inputs received duringa training session, such as heart rate (average) 170 measured by averagebeats per minute, heart rate variability (HRV) 170 measured by the timevariance in between each heartbeat, power (average) 170 measured by theaverage watts per workout. Combination cognitive and physical metricsmay be provided, such as rate of perceived exertion (RPE) 170 ascomputed from inputs provided during a self-assessment at the end of theworkout and Perception Gap (P-GAP) 168 computed by comparing theathlete's self-assessment inputs from the end of the workout 162, 164(FIG. 10 ) with their cognitive 168 and physical metrics 170 (FIG. 11 ).

FIG. 12 shows the athlete's cumulative report for all workouts over timethat includes a chart of their self-rated vs. physical performance overtime 174, a summary of their cognitive metrics for all workouts 176, alist of their top 3 mantras 178 and their top 5 best workouts 180 of alltime. Both the end of workout report (FIG. 11 ) and the summary of allworkouts over time (FIG. 12 ) utilize metrics, formulas and algorithmsbased on a series of lookup tables (FIG. 13 ). For example, ThePerception Gap (P-Gap) metric which is used to chart the athlete'smental endurance in 174 (FIG. 12 ) and their workout assessment 166(FIG. 11 ) uses lookup tables in FIG. 13 to compare their subjectiverate of perceived exertion (RPE) that they record at the end of theirworkout 162 (FIG. 10 ) with their expected RPE based on physiologicaloutput metrics recorded during the workout such as their average powerrecorded in watts 182 (FIG. 13 ) or average heart rate recorded in beatsper minute 186. For example, if the athlete's subjective RPE is 12 andtheir average power for the workout is 151 watts then the perception gapalgorithm first determines the athlete's expected RPE, by matching theiraverage power from the workout with the closest matching value in thelookup table 184 (FIG. 13 ). In this case, the athlete's average powermost closely matched an average FTP % of 55%, equivalent to an averagepower of 150 watts which corresponds to an expected RPE value of 9.Lastly, to determine the perception gap value the athlete's self-ratedRPE of 12 is subtracted from their expected RPE of 9 generating aperception gap score of −3. In other words, the athlete's subjectiverate of perceived exertion (RPE) was inflated by 3 points above whatshould be expected based on their physiological training output measuredin average power indicating that the athlete had a low level ofresistance to cognitive fatigue during training.

Another metric used to measure cognitive performance is called ReactionTime (RT) which is the time measured in seconds that it takes theathlete to respond correctly to a given cognitive task question. When acognitive task question is generated, a date object is created. Everytime an athlete answers a question, a time interval measuring thedifference between the date/time of when the question was asked and whenit was answered is saved in an array. At the end of the interval, theaverage values from this array are calculated and saved. At the end ofthe workout, the average response time is calculated for all of theintervals by iterating through intervals, adding the sum of the responsetimes (only if the interval average is greater than 0), and dividing bythe total number of these intervals.

Yet another metric used to measure cognitive performance is Accuracy(AC) which is the percentage of correct answers to cognitive questionscompared to the total number of questions for a given interval orworkout. Every time an athlete answers a question the softwaredetermines if the answer was correct or incorrect and saves the totalcorrect and total incorrect for current interval. At the end of theinterval, the total number of correct answers are added together and aredivided by the total number of answers then multiplied by 100 to createthe accuracy percentage score (AC). At the end of the workout, theaverage accuracy is calculated for all of the intervals by iteratingthrough intervals, adding the sum of the accuracy scores (only if theinterval average is greater than 0), and dividing by the total number ofthese intervals.

III. Motivational Self-Talk

Another feature supported within the custom software application is theintegration of self-talk mantras 188 (FIG. 14 ) that are designed toprovide psychological-based encouragement at specific intervals duringthe workout. In FIG. 15 the self-talk mantra feature can be configuredand personalized by the athlete with specific mantras 190 that arecreated by the athlete by pressing on the “+” symbol 194 in the topright corner of the screen, entering the mantra with the keyboard of asmartphone or a computer then selecting the mantra with the checkbox 192that is on the same line directly to the left of the mantra in order toenable it within the feature. The self-talk mantras are also capturedand correlated with real-time metrics and cognitive and physiologicalperformance metrics, formulas and algorithms in order to identify theefficacy of each mantra in terms of helping to improve the motivationand performance of the athlete. The top three mantras are then displayedon the cumulative report for all workouts over time 178 (FIG. 12 ).Additionally, the top performing mantras are adapted within the softwareto display at a higher frequency during the most difficult stages of theworkout to help improve the athlete's cognitive and physicalperformance. For example, if the athlete is under performing within acomplex cognitive task or physically demanding target goal the softwarewill briefly interrupt the workout in order to display a specific mantrathat in prior workouts has been correlated with better performance.After the mantra is displayed the software will further score themantra's efficacy in terms of its impact in improving performance withina short time period after it is displayed.

IV. Cognitive Recovery

At various times during or after brain training the athlete may engagewith different combinations of cognitive recovery and motivationprotocols (FIGS. 16A and 16B). In the case of using cognitive recoveryduring training, an athlete may use one or more of the recoveryprotocols during the rest period between training intervals or aspreparation for competition as part of the warm up or warm down processduring training. In the case of using cognitive recovery after a braintraining session, an athlete may use one or more of the recoveryprotocols as a form of recuperation after a difficult brain trainingworkout. The recovery protocols can be selected from the recoverycategory screen 206 (FIG. 16A) and include recovery protocol optionssuch as guided breathing 196, visualization 198, binaural beats 200,subliminal priming 202 and self-talk mantras 204. The recovery andmotivation software combines these different recovery protocols into asingle interface 208 (FIG. 16B) which is capable of playing eachprotocol in a sequence one after another based on a predeterminedpattern for each recovery session. The recovery and motivation softwarethen uses a series of metrics, formulas and algorithms to combine theathlete's self-rated metrics with the real-time cognitive andphysiological output metrics to provide reports (FIG. 17 ) thatsummarize the athlete's level of recovery during each session and overtime as well as a chart showing the proportions of each recoveryprotocol featured in the completed recovery session 210. For example, inorder to calculate the athlete's subjective self-rated level ofrelaxation found within the “Recovery Assessment” portion of the report212, the athlete is asked at both the start and end of each cognitiverecovery session to rate their current level of relaxation on a scale of1-10 where 1 equals “not relaxed” and 10 equals “extremely relaxed”. Thepercent change is then calculated between the athlete's self-rating atthe start and end of the session by dividing the absolute value of thedifference between the two numbers by the average of those two numbersthen multiplying the result by 100 to yield the percent difference e.g.“Your self-rated level of relaxation improved by 85%”. For the sectionof the report labeled “Recovery Summary” 214, various physiologicalmetrics are provided to show the level of physical recovery includingheart rate, heart rate range and heart rate variability (HRV). Heartrate is calculated by recording the athlete's heart rate beats perminute (BPM) using an external heart rate monitor or strap that ispaired with the recovery software then by calculating the average heartrate by taking the sum of all heart rate values divided by the totalnumber of values. Heart rate range is calculated by an algorithm thatscans all of the individual heart rate values and sorts them from thelowest to the highest then takes the first and last values to representthe heart rate range e.g. lowest heart rate value compared to highestheart rate value. Heart rate variability (HRV) is calculated by analgorithm which first measures the time interval between heart beats inmilliseconds, then calculates each successive time difference betweenheartbeats in milliseconds, then squares each of the values, thenaverages the result, then calculates the square root of the totalresult, then applies a natural logarithm and lastly applies a scalefactor to the logarithm in order to create 0-150 point scale to bedisplayed in the recovery summary report. An interval summary is alsoprovided within the “Recovery Intervals” section of the report 216,which lists metrics for each interval such as the total number ofseconds, total number of sets or cycles of the given protocol, the heartrate (average) for each interval, and the HRV for each interval. All ofthe metrics provided in the recovery report (FIG. 17 ) are comparedagainst a baseline average for each individual metric and the positiveor negative percent change of each measure factored into the software'sevaluation of the effectiveness of the recovery session for the athlete.

V. Cognitive Fatigue Assessment

At various times during or after brain training the athlete may completea cognitive fatigue self-assessment test (FIGS. 18A and 18B) in order tounderstand their current level of mental fatigue when compared to theirbaseline. The software will continuously adapt to the results of thecognitive assessments completed by the athlete, for example if theathlete completes a cognitive fatigue assessment with a resultindicating that there has been a decline in their cognitive performancethen the software will adapt to recommend an increase in the frequencyof cognitive recovery sessions and a decrease in the number of cognitivebrain training workouts. As the athlete's cognitive assessment scoresimprove the software will increase the recommendation to add morecognitive brain training workouts in order to optimize the volume ofcognitive stimuli for athletic performance. The cognitive fatigueself-assessment test works by providing output to a user guiding theuser through a cognitive testing protocol, such as is illustrated onuser interface 218 (FIG. 18A), such as a short reaction time or Go/No Gocognitive task combined with psychological-based questions 220 (FIG.18B) and physiological measures such as average heart rate and heartrate variability (HRV). For example, as part of a cognitive fatigueassessment, an athlete may complete a short cognitive test such as asimple reaction time test, as illustrated on user interface 218, wherethe athlete presses one of the tactile-based input apparatus buttonsevery time they see any stimulus such as a predetermined shape or set ofalphanumeric characters. After completing the short cognitive test theywill also be asked several psychological questions 220 such as howrested they feel 220, their level of readiness to perform athletictraining 220, their current level of stress 220 and current level offrustration 220. In this example, user inputs representing answers topsychological questions will be acquired with software rendering asliding input scale such as a visual analog scale 220 with simple tickmarks indicating levels of gradation from very low to very high.Alternatively or additionally, the fatigue assessment system may measurethe athlete's physiological metrics such as their average heart rate,heart rate variability (HRV) and other related physiological measuresfor the duration of the test. All of these data points may then be usedto compare against the athlete's baseline average from previous tests toprovide an overall cognitive fatigue score along with a cognitivetraining and recovery recommendation so that the athlete can assesstheir current state of readiness to perform a training workout orcompete in a competitive event. The recommendations provided as part ofthe cognitive assessment based on the overall cognitive fatigue scoremay also be used by the software to adjust the level of difficulty ofthe cognitive tasks by increasing or decreasing the level of complexityof the task questions, increasing or reducing the amount of time allowedfor each question and increasing or decreasing the target score neededto successfully complete a given cognitive task. The software may alsoadjust the default recommendations for cognitive recovery protocolsbased on the cognitive fatigue assessment score by increasing ordecreasing the default recovery session length and automaticallyprioritizing certain recovery protocols based on the athlete's needs.

VI. Flowchart of Software Operations

FIG. 19 shows a select sequence of operational steps describing how thesoftware of an athletic training system works. First, thesystem/application is turned on 222. Next the system checks for dataupdates from the cloud service 224, next any cloud data updates aresynchronized with the local database 226. The system scans forcompatible wireless brain training and biometric devices such as a powermeter or heart rate monitor 228, and the system pairs with compatiblewireless devices 230. The system processes coded messages sent fromwireless brain training and biometric devices in real time 232. Thesystem logic determines if coded messages sent from the wireless braintraining device(s) represent correct or incorrect answers to thecognitive task questions for the duration of the workout or recoverysession 234, next the system processes and stores all results in thelocal and cloud database 236, next the system performs finalcalculations at the end of the workout or recovery session 238 and lastthe system generates final reports that are saved to the local and clouddatabases 240.

Additional alternative embodiments of an athletic training system couldbe created by eliminating all external input devices and relying solelyon the built-in sensors and input systems found on a portable computingdevice such as a smartphone. Such a solution would rely on sensors builtinto the computing device such as accelerometers, gyroscopes and orcapacitive touch screens to provide manual and automated input methodsfor answering cognitive test questions. For example an athlete may tapon or tilt the screen of a remote computing device in a specific way inorder to respond to cognitive test questions during training. In thisexample, the movement or taps on the screen could be interpreted by thesoftware running on the remote computing device by accessing its sensordata and translating it to the corresponding correct or incorrectanswers during cognitive testing. The built-in sensors on the remotecomputing device may also be used to receive and interpret actions madeexternal to the computing device itself as a method for answeringcognitive test questions. For example, the athlete may double tap on thehandlebars of their bicycle trainer with their fingers while theportable computing device is mounted to the handlebars. In this example,a double tap on the handlebars by the athlete could be sensed byaccelerometer and gyroscope on the portable computing device andinterpreted by the custom software that is part of the athletic trainingsystem as representing correct or incorrect answers to cognitive testquestions during training.

An athletic training system may also be integrated into other trainingor psychological-based software and hardware to further extend itscapabilities or accessibility to athletes for specific sports. Forinstances where software for guiding a user through cognitive tasks,physical training and/or other actions as described above, is integratedinto other software or hardware systems, the input methods for answeringcognitive test questions during training may change in order to adapt tothe parent software and or hardware being used by the athlete.

The athletic training system described herein could also be adapted as atool for cognitive therapy for patients suffering from cognitivedeficits and disorders such as Parkinson's, ADHD, PTSD, OCD and AutismSpectrum Disorder where inhibitory control and cognitive function havebeen compromised.

The embodiments above are intended to be illustrative and not limiting.Additional embodiments are within the claims. In addition, although anathletic training system has been described with reference to particularembodiments, those skilled in the art will recognize that changes can bemade in form and detail without departing from the spirit and scope ofthe invention. Thus, the scope of the embodiments should be determinedby the appended claims and their legal equivalents, rather than by theexamples given.

Example Embodiments

Techniques as described herein may be applied in a method for assessingan athlete's level of cognitive fatigue. The method may comprise:receiving through an interface user responses as a user is guided toperform cognitive tasks; assessing level of cognitive and physicalstress based on one or more user inputs in response to prompts presentedto the user, the user responses and physiological measurements;assessing the user's cognitive fatigue and outputting a summary of theathlete's cognitive fatigue.

DRAWINGS—REFERENCE NUMERALS

-   -   100 a bicycle strap for tactile button    -   100 b hand strap for tactile button    -   102 tactile button    -   104 button cap    -   106 waterproof PCB enclosure (top)    -   108 printed circuit board (PCB)    -   110 battery    -   112 waterproof PCB enclosure (bottom)    -   114 clip for bicycle strap for tactile button    -   116 bicycle tactile button and strap    -   118 hand tactile button and strap    -   120 gesture-based input apparatus    -   122 motion sensors for gesture-based glove    -   124 voice commands from user sent to software    -   126 software interpreting voice commands    -   128 smartphone computer microphone    -   130 software interpreting wireless signals    -   132 smartphone computer receiving Bluetooth wireless signals    -   134 selection of brain training workouts    -   136 15 point scale for rating of perceived exertion (RPE)    -   138 example of level of effort value that the athlete is        challenged to produce    -   140 Example of cognitive task called a Stroop Task    -   142 left answer button    -   144 heads up display of target physiological output goals    -   146 right answer button    -   148 real-time physiological output metrics    -   150 software interpreting wireless commands    -   152 progress bar with target physiological output goals    -   154 progress bar at rest with 0% value    -   156 progress bar at 50%    -   158 progress bar at 100%    -   160 progress bar at above 100%    -   162 quantitative rating of perceived exertion (RPE) question    -   164 qualitative psychological questions    -   166 workout assessment    -   168 cognitive metrics    -   170 physical metrics    -   172 workout intervals    -   174 chart of self-rated vs. physical performance    -   176 summary of cognitive metrics for all workouts    -   178 top mantras    -   180 top 5 best workouts    -   182 functional threshold power (FTP) lookup table    -   184 example of average athlete power and RPE values    -   186 lactate threshold heart rate (LTHR) lookup table    -   188 self-talk mantras interface displayed during workout    -   190 example of self-talk mantra    -   192 check box enabling specific self-talk mantra    -   194 plus symbol for adding new self-talk mantras    -   196 guided breathing recovery example    -   198 visualization recovery example    -   200 binaural beats recovery example    -   202 subliminal priming recovery example    -   204 self-talk mantras recovery example    -   206 recovery category selection screen    -   208 recovery interface showing how self-talk mantras and        subliminal priming protocols    -   210 recovery chart showing the proportions of each recovery        protocol    -   212 recovery assessment    -   214 recovery summary    -   216 recovery intervals    -   218 cognitive testing protocol for fatigue assessment    -   220 psychological questions for fatigue assessment    -   222 system/application is turned on    -   224 system checks for data updates from cloud service    -   226 cloud data updates are synchronized with local database    -   228 system scans for compatible wireless devices    -   230 system pairs with compatible wireless devices    -   232 system processes coded messages sent from wireless devices    -   234 system logic determines correct and incorrect answers    -   236 system processes and stores all results in database    -   238 system performs final calculations at the end of the workout        or recovery session    -   240 system generates final reports that are saved to the local        and cloud databases.

What is claimed is:
 1. A method of operating an athletic training systemfor improving athletic performance by combining cognitive tasks withphysical training and recovery, the athletic training system comprisinga computer hardware processor, a user interface coupled to the computerhardware processor, and a device coupled to the computer hardwareprocessor and configured to receive input while a user is performing aphysical task, wherein the method comprises: using the computer hardwareprocessor to perform: presenting through the user interface a cognitivetask for the user to perform, wherein the presenting comprisesgenerating a cognitive task prompt prompting the user to provide aninput using the device; assessing cognitive and physical fatigue of theuser based on one or more inputs, wherein assessing cognitive fatiguecomprises processing the input received through the device inconjunction with the cognitive task prompt; identifying one or morecognitive recovery protocols based on the cognitive and physical fatigueof the user; and presenting through the user interface a prompt guidingthe user through a cognitive recovery protocol of the identified one ormore cognitive recovery protocols.
 2. The method of claim 1, furthercomprising: determining an order of the one or more recovery protocolsbased on the cognitive and physical fatigue of the user; and presentingthrough the user interface the one or more recovery protocols in thedetermined order.
 3. The method of claim 1, further comprising adjustinga length of a first recovery protocol of the one or more recoveryprotocols based on the cognitive and physical fatigue of the user. 4.The method of claim 1, wherein the cognitive task comprises one or moreof Stroop Task, Psychomotor Vigilance Task (PVT), Go/No Go Task,Continuous Performance Task (CPT), or Stop Signal Task.
 5. A method ofoperating an athletic training system for improving athletic performanceby combining cognitive tasks with physical training, the athletictraining system comprising a computer hardware processor, a userinterface coupled to the computer hardware processor, and a devicecoupled to the computer hardware processor and configured to receiveinput while a user is performing a physical task, wherein the methodcomprises: using the computer hardware processor to perform: presentingthrough the user interface a cognitive task for the user to perform,wherein the presenting comprises generating a cognitive task promptprompting the user to provide an input using the device; assessingcognitive and physical fatigue of the user, wherein assessing thecognitive fatigue of the user comprises processing the input receivedthrough the device in relation the cognitive task prompt; and outputtinga recommendation indicative of whether the user is ready to perform aworkout based at least in part on assessing the cognitive and physicalfatigue of the user.
 6. The method of claim 5, wherein assessing thecognitive fatigue of the user comprises: determining at least onecognitive metric based on the input received through the device inrelation to the cognitive task prompt; and comparing the at least onecognitive metric to at least one stored baseline metric.
 7. The methodof claim 6, wherein the at least one cognitive metric comprises one ormore of reaction time, accuracy, answer rate, or a metric indicative ofthe reaction time relative to an average reaction time.
 8. The method ofclaim 5, wherein assessing the physical fatigue of the user is performedusing a sensor coupled to the computer hardware processor, the assessingcomprising: capturing at least one physiological metric using thesensor; and comparing the at least one physiological metric to at leastone stored baseline metric.
 9. The method of claim 8, wherein the atleast one physiological metric comprises one or more of heart rate,heart rate variability (HRV), or functional threshold power.
 10. Themethod of claim 5, wherein outputting the recommendation indicative ofwhether the user is ready to perform the workout comprises: processingthe input received through the device in relation to the cognitive taskprompt and deriving a metric therefrom; and comparing the metric to afirst threshold indicative of readiness to compete and/or a secondthreshold indicative of readiness to perform a training workout.
 11. Themethod of claim 5, wherein outputting the recommendation indicative ofwhether the user is ready to perform the workout comprises presenting,through the user interface, a report indicating whether the user isready to perform the workout.
 12. The method of claim 5, furthercomprising modifying an aspect of the workout based at least in part onassessing the cognitive and physical fatigue of the user.
 13. The methodof claim 12, wherein the workout comprises one or more cognitive tasks,and wherein modifying the aspect of the workout comprises increasing ordecreasing a number of cognitive tasks included in the workout based onthe cognitive and physical fatigue of the user.
 14. The method of claim12, wherein the workout comprises one or more cognitive tasks, andwherein modifying the aspect of the workout comprises adaptingdifficulty of the one or more cognitive tasks based at least in part onthe cognitive and physical fatigue of the user.
 15. The method of claim14, wherein adapting the difficulty of a first cognitive task of the oneor more cognitive tasks comprises modifying the first cognitive task toadjust cognitive load for correctly responding to at least one cognitivetask prompt of a plurality of cognitive task prompts.
 16. The method ofclaim 14, wherein adapting difficulty of a first cognitive task of theone or more cognitive tasks comprises modifying an amount of time forresponding to at least one cognitive task prompt of a plurality ofcognitive task prompts.
 17. The method of claim 12, wherein the workoutcomprises one or more cognitive recovery protocols, and whereinmodifying the aspect of the workout comprises increasing or decreasing anumber of the one or more cognitive recovery protocols included in theworkout based at least in part on the cognitive and physical fatigue ofthe user.
 18. The method of claim 17, wherein a recovery protocol of theone or more recovery protocols comprises one or more of guidedbreathing, visualization, binaural beats, subliminal priming, orself-talk mantras.
 19. The method of claim 5, further comprisingmodifying an aspect of a recovery session based at least in part onassessing the cognitive and physical fatigue of the user, wherein therecovery session comprises one or more cognitive recovery protocols, andwherein modifying the aspect of the recovery session comprises adjustinga length of a first cognitive recovery protocol of the one or morecognitive recovery protocols based on the cognitive and physical fatigueof the user.
 20. The method of claim 19, wherein modifying the aspect ofthe recovery session further comprises performing one or more of:determining a temporal order in which the one or more cognitive recoveryprotocols should be presented through the user interface based on thecognitive and physical fatigue of the user and determining a durationduring which the one or more cognitive recovery protocols should bepresented through the user interface based on the cognitive and physicalfatigue of the user.
 21. The method of claim 5, further comprising:presenting, through the user interface, a psychological question for theuser to answer; and receiving input through the device in relation tothe psychological question, wherein outputting the recommendationindicative of whether the user is ready to perform a workout based atleast in part on assessing the cognitive and physical fatigue of theuser comprises outputting the recommendation based on the input receivedin relation to the psychological question.
 22. An athletic trainingsystem for improving athletic performance by combining cognitive taskswith physical training, the system comprising: a computer hardwareprocessor; a device coupled to the computer hardware processor andconfigured to receive input while a user is performing a physical task;a user interface coupled to the computer hardware processor; and anon-transitory computer-readable storage medium storing processorexecutable instructions that, when executed by the processor, cause thecomputer hardware processor to perform: presenting through the userinterface a cognitive task for the user to perform, wherein thepresenting comprises generating a cognitive task prompt prompting theuser to provide an input using the device; assessing cognitive andphysical fatigue of the user based on one or more inputs, whereinassessing cognitive fatigue comprises processing the input receivedthrough the device in conjunction with the cognitive task prompt;identifying one or more cognitive recovery protocols based on thecognitive and physical fatigue of the user; and presenting through theuser interface a prompt guiding the user through a cognitive recoveryprotocol of the identified one or more cognitive recovery protocols.